Nonlinear wavelet/wavelet packet (W/WP) estimators are becoming popular methods for image denoising. Most of the related works are based on a hard or soft thresholding of the W/WP coefficients. We present a new nonlinear estimation method whose characteristics are adapted to the statistics of the image under study. We describe the statistical problem which is addressed in this paper and present different methods for adaptive image denoising. We emphasize the shortcomings of classical threshold estimators and propose an alternative approach. We then illustrate the interest of our method by simulation examples on satellite images.
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机译:非线性小波/小波包(W / W / WP)估计成为图像去噪的流行方法。大多数相关工作基于W / WP系数的硬或软阈值。我们提出了一种新的非线性估计方法,其特征适应于正在研究的图像的统计数据。我们描述了本文解决的统计问题,并呈现了适应性图像去噪的不同方法。我们强调了经典门槛估计的缺点,并提出了一种替代方法。然后,我们通过卫星图像上的仿真示例说明我们的方法的兴趣。
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